Salary for Senior-level / Expert Data Engineer in Canada during 2024

Salary details

The average senior-level / expert Data Engineer salary lies between USD 103,846 and USD 171,210 in Canada. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Engineer roles

The three most common job tag items assiciated with senior-level / expert Data Engineer job listings are Engineering, Python and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 8786 jobs Python | 8337 jobs SQL | 8175 jobs Pipelines | 7412 jobs AWS | 5838 jobs Data pipelines | 5718 jobs ETL | 5599 jobs Architecture | 5546 jobs Spark | 5231 jobs Computer Science | 4744 jobs Big Data | 4283 jobs Azure | 4207 jobs Agile | 4061 jobs Security | 3843 jobs Machine Learning | 3584 jobs Java | 3343 jobs Data quality | 3287 jobs Airflow | 3118 jobs GCP | 3111 jobs Snowflake | 3005 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Data Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 6824 jobs Health care | 3699 jobs Flex hours | 2920 jobs Team events | 2202 jobs Competitive pay | 2075 jobs Startup environment | 2053 jobs Equity / stock options | 1967 jobs Salary bonus | 1679 jobs Flex vacation | 1672 jobs Insurance | 1539 jobs Parental leave | 1438 jobs Medical leave | 1243 jobs Wellness | 1028 jobs 401(k) matching | 828 jobs Fitness / gym | 416 jobs Gear | 375 jobs Home office stipend | 343 jobs Transparency | 341 jobs Conferences | 291 jobs Relocation support | 287 jobs

Salary Composition

In Canada, the salary composition for a Senior-level or Expert Data Engineer in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, might contribute around 10-15%. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5-10%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech companies in major cities like Toronto or Vancouver might offer higher base salaries and stock options, while smaller companies or those in less competitive regions might focus more on bonuses and benefits.

Increasing Salary Further

To increase your salary further from a Senior-level Data Engineer position, consider the following strategies:

• Specialization: Develop expertise in niche areas such as machine learning engineering, big data technologies, or cloud computing, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Engineering Manager or Director of Data Engineering, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data science. This can involve taking advanced courses or obtaining certifications.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends in the industry.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level Data Engineer positions require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles that involve complex data science and machine learning tasks. Advanced degrees can also provide a competitive edge and potentially lead to higher salaries.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Data Management Professional (CDMP)
• Google Professional Data Engineer
• AWS Certified Big Data – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications can validate your skills in specific technologies and platforms, making you a more attractive candidate for senior roles.

Required Experience

Typically, a Senior-level Data Engineer is expected to have at least 5-10 years of experience in data engineering or related fields. This experience should include a strong background in data architecture, ETL processes, data warehousing, and proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms like AWS, Azure, or Google Cloud is also highly desirable.

Related salaries

Want to contribute?